Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures | Paper Citation Record

Observation 1eb91de1-c76e-404e-bb19-dffe2af04597 · outbound

This paper cites Trusted multi-view classi- fication with dynamic evidential fusion,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Trusted multi-view classi- fication with dynamic evidential fusion,

Reference 1

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Observation b0de53cb-a0da-46d3-b9e7-9eaeb7df7250 · outbound

This paper cites Incomplete contrastive multi-view clustering with high-confidence guiding,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Incomplete contrastive multi-view clustering with high-confidence guiding,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:39.117917Z

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Observation 2e8c5423-fff3-488b-a16a-21649c4cb2cf · outbound

This paper cites Exploring and Exploiting Uncertainty for Incomplete Multi-View Classification,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Exploring and Exploiting Uncertainty for Incomplete Multi-View Classification,

Reference 3

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Observation 69ae9b1f-a2f6-49ec-9df3-6a1f87c226a9 · outbound

This paper cites Fast continual multi-view clustering with incomplete views,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Fast continual multi-view clustering with incomplete views,

Reference 4

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Observation 702e228b-b63c-476b-8edc-11e541516111 · outbound

This paper cites Self-supervised information bottleneck for deep multi-view subspace clustering,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Self-supervised information bottleneck for deep multi-view subspace clustering,

Reference 5

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Observation a4fba3a7-a976-41ca-a3c8-868bc0d51cf3 · outbound

This paper cites Posterior network: Uncertainty estimation without ood samples via density-based pseudo- counts,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Posterior network: Uncertainty estimation without ood samples via density-based pseudo- counts,

Reference 6

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Observation f5e3805e-23fd-4063-96ec-b4ea636570cf · outbound

This paper cites On the Dempster-Shafer framework and new combination rules,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures On the Dempster-Shafer framework and new combination rules,

Reference 8

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Observation 177425d6-e59c-47af-b991-c380955f9855 · outbound

This paper cites On H ¨older projective divergences,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures On H ¨older projective divergences,

Reference 9

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Observation 78d4eb8e-0754-4d55-ba95-3c04e122fc98 · outbound

This paper cites Bayesian filtering: From Kalman filters to particle filters, and beyond,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Bayesian filtering: From Kalman filters to particle filters, and beyond,

Reference 10

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Observation b85585c1-2287-4cab-a430-b2d46471ae6a · outbound

This paper cites I-divergence geometry of probability distributions and min- imization problems,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures I-divergence geometry of probability distributions and min- imization problems,

Reference 11

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Observation 94c4f065-cf85-429d-aeba-7ddb0672d6f9 · outbound

This paper cites Self-supervised geometric features discovery via interpretable attention for vehicle re-identification and beyond,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Self-supervised geometric features discovery via interpretable attention for vehicle re-identification and beyond,

Reference 12

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Observation b81c6625-b8e6-41e6-b767-4d2a7d7c185c · outbound

This paper cites Exploiting multi- view part-wise correlation via an efficient transformer for vehicle re- identification,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Exploiting multi- view part-wise correlation via an efficient transformer for vehicle re- identification,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:37.277022Z

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Observation 392f8f36-a6e1-473e-8023-eba6a060d245 · outbound

This paper cites Synthetic-to-real self-supervised robust depth estimation via learning with motion and structure priors,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Synthetic-to-real self-supervised robust depth estimation via learning with motion and structure priors,

Reference 14

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Observation 7dcc115b-6c2d-4a1b-a69e-c7c66dd1369c · outbound

This paper cites Eventgpt: Event stream understanding with multimodal large language models,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Eventgpt: Event stream understanding with multimodal large language models,

Reference 15

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Observation 5bf708bb-aadd-4262-9815-5ed15dfed5ce · outbound

This paper cites FaVChat: Hierarchical Prompt-Query Guided Facial Video Understanding with Data-Efficient GRPO.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures FaVChat: Hierarchical Prompt-Query Guided Facial Video Understanding with Data-Efficient GRPO

Reference 16

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Observation 11de69b8-a397-4a97-9446-2494bfdf9ad9 · outbound

This paper cites Unif2ace: Fine-grained face understanding and generation with unified multimodal models,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Unif2ace: Fine-grained face understanding and generation with unified multimodal models,

Reference 17

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Observation bfa1b76b-bb84-4bdd-bd00-b062d0a1994e · outbound

This paper cites Dr-fer: Discriminative and robust representation learning for facial expression recognition,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Dr-fer: Discriminative and robust representation learning for facial expression recognition,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:36.811947Z

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Observation 31fe00e8-044c-4a02-8cd8-36243abac0e7 · outbound

This paper cites Stprivacy: Spatio-temporal privacy-preserving action recognition,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Stprivacy: Spatio-temporal privacy-preserving action recognition,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:36.659610Z

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Observation ec8a1808-1a64-443d-88df-854ebc8c9c2e · outbound

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Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Instant3d: instant text-to-3d generation,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:36.517026Z

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Observation a82f1206-0aac-4829-b24f-a8048b37cbbe · outbound

This paper cites RealEra: Semantic-level Concept Erasure via Neighbor-Concept Mining.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures RealEra: Semantic-level Concept Erasure via Neighbor-Concept Mining

Reference 21

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Observation 48a50fe0-88e5-4f90-b289-2b83c8898434 · outbound

This paper cites Vistorybench: Comprehensive bench- mark suite for story visualization,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Vistorybench: Comprehensive bench- mark suite for story visualization,

Reference 22

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Observation 18bd2dc5-9331-4092-8ea4-09d3b96cd3da · outbound

This paper cites Reliable conflictive multi-view learning,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Reliable conflictive multi-view learning,

Reference 23

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Observation 6c5cd254-f2d7-4708-ab65-2f4c7835ee4e · outbound

This paper cites One-Step Multi-View Clustering With Diverse Representation,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures One-Step Multi-View Clustering With Diverse Representation,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:36.312663Z

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Observation 3f64da6e-9406-4dd3-a247-9c426e8bf06f · outbound

This paper cites Multi-view multi-label canonical correlation analysis for cross-modal matching and retrieval,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Multi-view multi-label canonical correlation analysis for cross-modal matching and retrieval,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:36.062091Z

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Observation a494d69d-1567-4c89-b8e8-71eea412b7ac · outbound

This paper cites A multi-view co-training network for semi-supervised medical image-based prognostic prediction,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures A multi-view co-training network for semi-supervised medical image-based prognostic prediction,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:35.798001Z

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Observation 9befe091-2e97-43de-9ba2-86b96ea1a229 · outbound

This paper cites Visual tracking with spatio-temporal Dempster–Shafer information fusion,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Visual tracking with spatio-temporal Dempster–Shafer information fusion,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:35.488793Z

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Observation 99aa1b23-92cd-4ada-89f5-a231dc42df4a · outbound

This paper cites Variational Quantum Linear Solver-based Combination Rules in Dempster–Shafer Theory,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Variational Quantum Linear Solver-based Combination Rules in Dempster–Shafer Theory,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:35.148661Z

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Observation 2920c954-7386-43b8-bbe5-7342923499b0 · outbound

This paper cites Scale-invariant divergences for density functions,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Scale-invariant divergences for density functions,

Reference 29

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Observation 8ee2219c-875e-4f6a-b956-62a21ad57e35 · outbound

This paper cites The Cauchy– Schwarz divergence for Poisson point processes,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures The Cauchy– Schwarz divergence for Poisson point processes,

Reference 30

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Observation 878d72c3-16b0-4a5e-9f28-b3bb030f7bb6 · outbound

This paper cites K-means clustering with H ¨older divergences,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures K-means clustering with H ¨older divergences,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:34.043752Z

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Observation 8abb0ea8-ce51-448e-8674-565b262b1722 · outbound

This paper cites Classification for Polsar image based on h ¨older divergences,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Classification for Polsar image based on h ¨older divergences,

Reference 32

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Observation e3ddd8d8-1ade-4bed-8fae-f182c118d66d · outbound

This paper cites Inverse kalman filtering problems for discrete-time systems,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Inverse kalman filtering problems for discrete-time systems,

Reference 33

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Observation d35c7c3c-c2bf-41ac-bca9-0151eb640f9e · outbound

This paper cites Adaptive kalman filtering for histogram-based appearance learn- ing in infrared imagery,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Adaptive kalman filtering for histogram-based appearance learn- ing in infrared imagery,

Reference 34

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Observation 8e73952d-5f1d-404c-bb96-6641dfada5e5 · outbound

This paper cites Efficient and fast real-world noisy image denoising by combining pyramid neural network and two-pathway unscented Kalman filter,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Efficient and fast real-world noisy image denoising by combining pyramid neural network and two-pathway unscented Kalman filter,

Reference 35

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Observation 8f7f0224-75df-45be-b55c-5874f4d054fd · outbound

This paper cites Kalman filter for spatial- temporal regularized correlation filters,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Kalman filter for spatial- temporal regularized correlation filters,

Reference 36

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Observation 30d044ac-b5d9-4572-b9bb-9cbbcb286dc7 · outbound

This paper cites The statistical analysis of compositional data,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures The statistical analysis of compositional data,

Reference 37

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Observation ab456d37-a73a-4b1a-bf04-27541ca859f1 · outbound

This paper cites Dirichlet and related distribu- tions: Theory, methods and applications,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Dirichlet and related distribu- tions: Theory, methods and applications,

Reference 38

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Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Unresolved cited work

Reference 39

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Observation 5d85d5bf-b1c0-42c8-b4b9-7a609897e6b2 · outbound

This paper cites Clustering documents with an exponential-family approxima- tion of the Dirichlet compound multinomial distribution,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Clustering documents with an exponential-family approxima- tion of the Dirichlet compound multinomial distribution,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:31.698124Z

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Observation df13ebc0-608b-4d8f-913e-5d03f5f42079 · outbound

This paper cites Jsang, Subjective Logic: A formalism for reasoning under uncertainty.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Jsang, Subjective Logic: A formalism for reasoning under uncertainty

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:38.179106Z

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Observation a47d7371-d631-487b-bf58-dbf11bb1b8f5 · outbound

This paper cites Belief functions and parametric models,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Belief functions and parametric models,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:31.565938Z

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Observation 999ecc0f-605d-46a3-9dff-8a3e9c0eb6c8 · outbound

This paper cites A Dempster-Shafer Approach to Trustworthy AI With Application to Fetal Brain MRI Segmentation,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures A Dempster-Shafer Approach to Trustworthy AI With Application to Fetal Brain MRI Segmentation,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:31.387986Z

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Observation b7e56cb3-ee9c-4afe-8aec-0d346e8f43b7 · outbound

This paper cites Multimodal Dy- namics: Dynamical Fusion for Trustworthy Multimodal Classification,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Multimodal Dy- namics: Dynamical Fusion for Trustworthy Multimodal Classification,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:31.235174Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c041a443-cb90-4bcd-b833-9295bdd492eb · outbound

This paper cites Cauchy–Schwarz Regularized Autoencoder,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Cauchy–Schwarz Regularized Autoencoder,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:31.091810Z

Source-reported events for the cited work

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Observation a4819b35-e03b-49b5-92f3-6d6ead748ebb · outbound

This paper cites Sun RGB-D: A RGB-D scene understanding benchmark suite,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Sun RGB-D: A RGB-D scene understanding benchmark suite,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:30.931423Z

Source-reported events for the cited work

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Observation 78c30408-3026-4f1e-ab0a-8821504c0d27 · outbound

This paper cites Indoor segmentation and support inference from rgbd images,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Indoor segmentation and support inference from rgbd images,

Reference 47

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Source-reported events for the cited work

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Observation 7adae435-1993-406f-8c1b-b66aa83ac31a · outbound

This paper cites Semantic understanding of scenes through the ade20k dataset,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Semantic understanding of scenes through the ade20k dataset,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:30.772098Z

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Observation f879c8ef-fc24-4ecd-8e86-9f912ae6603f · outbound

This paper cites Scannet: Richly-annotated 3D reconstructions of indoor scenes,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Scannet: Richly-annotated 3D reconstructions of indoor scenes,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:30.620474Z

Source-reported events for the cited work

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Observation 5baef114-3212-45c0-9ee4-5448e3f372ec · outbound

This paper cites Parameter-free auto-weighted multiple graph learning: A framework for multiview clustering and semi-supervised classification.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Parameter-free auto-weighted multiple graph learning: A framework for multiview clustering and semi-supervised classification

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:30.427087Z

Source-reported events for the cited work

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Observation 1129e0f4-96a7-47c0-976c-8d33c662299b · outbound

This paper cites A fast iterative shrinkage-thresholding algo- rithm for linear inverse problems,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures A fast iterative shrinkage-thresholding algo- rithm for linear inverse problems,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:30.291741Z

Source-reported events for the cited work

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Observation 618eb559-5fa2-4e5e-8975-90851cbefd68 · outbound

This paper cites Unsupervised video matting via sparse and low-rank representation,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Unsupervised video matting via sparse and low-rank representation,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:30.088411Z

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Observation 2bab2c6b-4106-453f-99e3-20c206d27026 · outbound

This paper cites DasGupta, Probability for statistics and machine learning: fundamentals and advanced topics.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures DasGupta, Probability for statistics and machine learning: fundamentals and advanced topics

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:29.614335Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 22f78378-e82f-4472-b177-8973ff162dba · outbound

This paper cites Learning deep sparse regu- larizers with applications to multi-view clustering and semi-supervised classification,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Learning deep sparse regu- larizers with applications to multi-view clustering and semi-supervised classification,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:29.287889Z

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Observation 95922390-4399-4476-847f-84c983863cfe · outbound

This paper cites Deep residual learning for image recognition,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Deep residual learning for image recognition,

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-06T17:48:21.338635Z

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Observation 5405516f-e57d-43eb-9271-fd5378f828db · outbound

This paper cites ImageNet: A large-scale hierarchical image database,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures ImageNet: A large-scale hierarchical image database,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:28.903353Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b05b5dbb-f917-4712-8719-0aad31acaace · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures U-net: Convolutional networks for biomedical image segmentation,

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-06T17:48:21.505363Z

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Observation 25ce883f-7135-42d7-adf9-8d810b4c134e · outbound

This paper cites Densely connected convolutional networks,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Densely connected convolutional networks,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:28.556382Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 412ac5ea-bed6-444b-9d7e-8985ab6cea11 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:28.184145Z

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Observation 2e66b3bb-a7bf-4883-ac39-94223b87599b · outbound

This paper cites Hungry Hungry Hippos: Towards Language Modeling with State Space Models,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Hungry Hungry Hippos: Towards Language Modeling with State Space Models,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:27.828260Z

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Observation 350aa3d7-add4-4e39-8105-5832ed60997f · outbound

This paper cites Adam: A Method for Stochastic Optimiza- tion,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Adam: A Method for Stochastic Optimiza- tion,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:27.573065Z

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Observation fc0e7d99-1bc1-4bf0-9c86-8c8b63ef0b85 · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Pytorch: An imperative style, high-performance deep learning library,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:27.326029Z

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Observation b13e6cb8-3e65-49cf-9bf3-29c70e90982e · outbound

This paper cites Translate-to- recognize networks for RGB-D scene recognition,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Translate-to- recognize networks for RGB-D scene recognition,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:27.084090Z

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Observation 57639c06-a768-4832-a854-87dfd1456dca · outbound

This paper cites Image rep- resentations with spatial object-to-object relations for RGB-D scene recognition,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Image rep- resentations with spatial object-to-object relations for RGB-D scene recognition,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:26.832597Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6bab63d6-5f84-4ef0-9c44-6a769f63fb2a · outbound

This paper cites Centroid Based Concept Learning for RGB-D Indoor Scene Classification,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Centroid Based Concept Learning for RGB-D Indoor Scene Classification,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:26.559654Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 97a294d4-e439-4877-86db-c5cfb3e05046 · outbound

This paper cites Cross-modal pyramid translation for RGB-D scene recognition,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Cross-modal pyramid translation for RGB-D scene recognition,

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:26.448802Z

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Observation 3c8cf367-55ed-49a0-882c-e7052762c174 · outbound

This paper cites When CNNs meet random RNNs: Towards multi-level analysis for RGB-D object and scene recognition,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures When CNNs meet random RNNs: Towards multi-level analysis for RGB-D object and scene recognition,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:26.292694Z

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Observation 8ec85c31-fd83-4c95-98e6-7e5ab68fbbb7 · outbound

This paper cites FGMNet: Feature grouping mechanism network for RGB-D indoor scene semantic seg- mentation,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures FGMNet: Feature grouping mechanism network for RGB-D indoor scene semantic seg- mentation,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:26.124100Z

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Observation 2455e7cd-63ed-402c-a568-3b68fc34bbfe · outbound

This paper cites Feature contrast difference and enhanced network for rgb-d indoor scene classification in internet of things,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Feature contrast difference and enhanced network for rgb-d indoor scene classification in internet of things,

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:25.851072Z

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Observation e3355632-b8bd-4f76-ac8e-67b1b47badc0 · outbound

This paper cites An efficient k-means clustering algorithm: Analysis and implementation,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures An efficient k-means clustering algorithm: Analysis and implementation,

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:25.639833Z

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Observation cc540381-bfd4-49b2-8292-8355262b8c50 · outbound

This paper cites Self-weighted multiview clustering with multiple graphs.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Self-weighted multiview clustering with multiple graphs

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:29.926185Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5c3cf413-555d-46b5-a7bb-673d1980bc62 · outbound

This paper cites Multi-view clustering and semi-supervised classification with adaptive neighbours,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Multi-view clustering and semi-supervised classification with adaptive neighbours,

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:25.486531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bcde998e-a90c-4540-9ccf-d5841aab0ffb · outbound

This paper cites Multiview consensus graph clustering,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Multiview consensus graph clustering,

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:25.280315Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 307427cf-36d1-44cd-8b01-c37eaf2b4539 · outbound

This paper cites Binary multi- view clustering,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Binary multi- view clustering,

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:25.035542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation df973c27-28a9-4cfa-8a06-316e9d53828d · outbound

This paper cites Multi-view subspace clustering with intactness-aware similarity,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Multi-view subspace clustering with intactness-aware similarity,

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:24.785009Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2e4549f2-ff95-475b-8911-5a32f70a57ed · outbound

This paper cites Multi-view clustering based on view-attention driven,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Multi-view clustering based on view-attention driven,

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:24.673930Z

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Observation ee2a36c0-e7dc-4555-9f2b-98d12ef32572 · outbound

This paper cites One for all: A novel Dual-space Co-training baseline for Large-scale Multi-View Clustering.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures One for all: A novel Dual-space Co-training baseline for Large-scale Multi-View Clustering

Reference 78

Resolution: verified exact; local_arxiv, observed 2026-08-06T17:48:23.561827Z

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Observation ec2cbf74-2d3c-46d9-922a-18bd8322f5b4 · outbound

This paper cites Deep Incomplete Multi-View Learning Network with Insufficient Label Information,.

Uncertainty Quantification for Incomplete Multi-View Data Using Divergence Measures Deep Incomplete Multi-View Learning Network with Insufficient Label Information,

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:24.482279Z

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